Abstract
The South Atlantic Convergence Zone (SACZ) plays a key role in the South American monsoon system (SAMS) precipitation regime, and accounts for around 25% of the rainfall volume over Southeast Brazil between October and April, on average, with peaks of 56% in March and 41% in January. Due to its often varying position and multi-variable structure, diagnosing or quantifying SACZ episodes may lie on subjective criteria. The present study provides a climatological characterization of different SACZ types, based on their position, and differences in dynamics analysed from 19 SAMS wet periods. A cycle in SACZ configurations is identified during the rainy season: northernmost (southernmost) episodes are more likely to occur during the onset/demise (peak) months of the SAMS. Objective SACZ indices are developed taking the principal components of the dynamics of the SACZ as explanatory variables, not including precipitation. The most sensitive threshold proposed for the identification of mean SACZ type yields simultaneous true positive rate of 86%, false alarm rate of 28%, true negative rate of 72% and false negative rate of 15%, for example. The indices have potential to bring gains in predictability to SACZ-related precipitation in Southeast Brazil, apart from allowing the objective diagnosis of SACZ episodes. The indices are also correlated with the South American precipitation dipole and may be used to identify anomalous SAMS precipitation at longer time scales as well.
Highlights
The configuration of a South Atlantic Convergence Zone (SACZ) episode is triggered by the presence of a Frontal System (FS) and its associated trough in around 500 hPa, whose position responds to remote disturbances in the South Pacific Convergence Zone (SPCZ) region, as early discussed by Grimm and Silva Dias (1995), and to the propagation of extratropical Rossby wave trains in a Pacific-South American (PSA) teleconnection pattern (Liebmann et al 1999, 2004; Nogués-Paegle et al 2000; Muza et al 2009; van der Wiel et al 2015)
A daily operational use of the indices requires that their continuous values are transformed back into a binary response, which demands that objective decision thresholds, or operating cut-off limits, are determined: outcomes greater than h are classified as positive (SACZ occurs) and outcomes less than h are classified as negative (SACZ does not occur)
19 wet periods of the South American monsoon system (SAMS) are examined and three modes of SACZ configurations are defined in terms of the latitudinal variation of its cloud band position: northernmost (AB), mean (C) and southernmost (DE) SACZ types
Summary
Two main large-scale characteristics of the South American monsoon system (SAMS) are the reversion in direction of low-level wind anomalies between austral summer and winter followed by an seasonal meridional movement of rainfall maxima over South America (SA) (Zhou and Lau 1998; Gan et al 2004; Vera et al 2006), associated with the annual cycle of mainly two different mechanisms, namely: (1) the Intertropical Convergence Zone (ITCZ) meridional shift over northern SA and (2) the South Atlantic Convergence Zone (SACZ), extending from the southern Amazonian region to central-eastern SA and the neighbouring portion of the Atlantic Ocean, drawing a characteristic quasi-stationary diagonally-oriented cloud band region in the Northwest-Southeast (NW-SE) direction (Kodama 1992, 1993; Quadro 1994). Convection is increased over the continent during summer, leading to the Under these conditions, the configuration of a SACZ episode is triggered by the presence of a Frontal System (FS) and its associated trough in around 500 hPa, whose position responds to remote disturbances in the South Pacific Convergence Zone (SPCZ) region, as early discussed by Grimm and Silva Dias (1995), and to the propagation of extratropical Rossby wave trains in a Pacific-South American (PSA) teleconnection pattern (Liebmann et al 1999, 2004; Nogués-Paegle et al 2000; Muza et al 2009; van der Wiel et al 2015). About 70% of the Brazilian electrical energy sources rely on hydropower generation (ONS 2015) For this reason, relatively small variations in the SACZ position may determine which river basins are supplied with rainfall and which other regions experience drier conditions, influenced by atmospheric subsidence and surface highs. Lead 1 is composed as a mean of the results from 24, 30, 36 and 42 h after the 00UTC initialization, Lead 4: 96, 102, 108 and 114 h, and Lead 7: 168, 174, 180 and 186 h after initialization
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